Mateo Valero on how the MareNostrum 4 Supercomputer will Advance Science

In this video from ISC 2017, Mateo Valero from the Barcelona Supercomputing Center describes the innovations behind MareNostrum 4, the #13 supercomputer on the TOP500.

“MareNostrum 4, hosted by Barcelona Supercomputing Center, is entirely aimed at generating scientific knowledge and its computer architecture has been called ‘the most diverse and interesting in the world’ by international experts. Equipped with Intel’s latest processing and networking technologies, MareNostrum provides 11.1 Petaflops of processing power to scientific production. This is the capacity of the general-purpose cluster, the largest and most powerful part of the supercomputer, which will be increased thanks to the installation of three new, smaller-scale clusters, featuring emerging technologies, over the next few months. The capacity of 11.1 Petaflops is 10 times greater than that of MareNostrum 3, which was installed between 2012 and 2013.

According to the Top500 ranking published on 19 June, the MareNostrum 4 supercomputer’s general-purpose cluster is the third most powerful one in Europe and the thirteenth in the world. The Top500 list is based on how quickly supercomputers execute the high-performance linpack benchmark.”

Resource Links:

Latest Video

Industry Perspectives

In this podcast, Terri Quinn from LLNL provides an update on Hardware and Integration (HI) at the Exascale Computing Project. "The US Department of Energy (DOE) national laboratories will acquire, install, and operate the nation’s first exascale-class systems. ECP is responsible for assisting with applications and software and accelerating the research and development of critical commercial exascale system hardware. ECP’s Hardware and Integration research focus area (HI), was created to help the laboratories and the ECP teams achieve success through mutually beneficial collaborations." [Read More...]

White Papers

Deep learning and complex machine learning has quickly become one of the most important computationally intensive applications for a wide variety of fields. Download the new paper — from Advanced Micro Devices Inc. (AMD) and Xilinx Inc. — that explores the challenges of deep learning training and inference, and discusses the benefits of a comprehensive approach for combining CPU, GPU, FPGA technologies, along with the appropriate software frameworks in a unified deep learning architecture.